Instructions to use rehanhaider/vectors-training-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rehanhaider/vectors-training-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rehanhaider/vectors-training-sdxl-1.0") prompt = "in the style of wlat_mntn" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit ·
75e84bb
1
Parent(s): 955f998
End of training
Browse files- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_lora_weights.bin +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +1 -1
- checkpoint-500/pytorch_lora_weights.bin +1 -1
- checkpoint-500/random_states_0.pkl +2 -2
- image_0.png +2 -2
- image_1.png +2 -2
- image_2.png +2 -2
- image_3.png +2 -2
- logs/dreambooth-lora-sd-xl/1690583145.9043336/events.out.tfevents.1690583145.fd8329d6d285.8206.1 +3 -0
- logs/dreambooth-lora-sd-xl/1690583145.9062133/hparams.yml +52 -0
- logs/dreambooth-lora-sd-xl/events.out.tfevents.1690583145.fd8329d6d285.8206.0 +3 -0
- pytorch_lora_weights.bin +1 -1
checkpoint-1000/optimizer.bin
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checkpoint-1000/pytorch_lora_weights.bin
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checkpoint-1000/scheduler.bin
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checkpoint-1500/optimizer.bin
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checkpoint-1500/pytorch_lora_weights.bin
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checkpoint-1500/random_states_0.pkl
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checkpoint-1500/scheduler.bin
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checkpoint-500/optimizer.bin
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checkpoint-500/pytorch_lora_weights.bin
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image_0.png
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logs/dreambooth-lora-sd-xl/1690583145.9043336/events.out.tfevents.1690583145.fd8329d6d285.8206.1
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logs/dreambooth-lora-sd-xl/1690583145.9062133/hparams.yml
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adam_beta1: 0.9
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adam_beta2: 0.999
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adam_epsilon: 1.0e-08
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adam_weight_decay: 0.01
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allow_tf32: false
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center_crop: false
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checkpointing_steps: 500
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checkpoints_total_limit: null
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class_data_dir: null
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class_prompt: null
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crops_coords_top_left_h: 0
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crops_coords_top_left_w: 0
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dataloader_num_workers: 0
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enable_xformers_memory_efficient_attention: false
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gradient_accumulation_steps: 4
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gradient_checkpointing: false
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hub_model_id: null
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hub_token: null
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instance_data_dir: training_images
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instance_prompt: in the style of wlat_mntn
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learning_rate: 1.0e-06
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local_rank: -1
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logging_dir: logs
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lr_num_cycles: 1
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lr_power: 1.0
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lr_scheduler: constant
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lr_warmup_steps: 0
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max_grad_norm: 1.0
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max_train_steps: 1600
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mixed_precision: fp16
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num_class_images: 100
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num_train_epochs: 400
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num_validation_images: 4
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output_dir: vectors-training-sdxl-1.0
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pretrained_model_name_or_path: stabilityai/stable-diffusion-xl-base-1.0
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pretrained_vae_model_name_or_path: null
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prior_generation_precision: null
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prior_loss_weight: 1.0
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push_to_hub: true
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report_to: tensorboard
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resolution: 1024
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resume_from_checkpoint: null
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revision: null
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sample_batch_size: 4
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scale_lr: false
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seed: 0
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train_batch_size: 1
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train_text_encoder: false
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use_8bit_adam: false
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validation_epochs: 25
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validation_prompt: illustration of a tree in the style of wlat_mntn
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with_prior_preservation: false
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logs/dreambooth-lora-sd-xl/events.out.tfevents.1690583145.fd8329d6d285.8206.0
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size 8831958
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pytorch_lora_weights.bin
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